Publications (6)
GOOD: Towards Domain Generalized Orientated Object Detection
Qi Bi, Beichen Zhou, Jingjun Yi +3
Oriented object detection has been rapidly developed in the past few years, but most of these methods assume the training and testing images are under the same statistical distribu…
Attention Awareness Multiple Instance Neural Network
Jingjun Yi, Beichen Zhou
Multiple instance learning is qualified for many pattern recognition tasks with weakly annotated data. The combination of artificial neural network and multiple instance learning o…
A Multi-Stage Duplex Fusion ConvNet for Aerial Scene Classification
Jingjun Yi, Beichen Zhou
Existing deep learning based methods effectively prompt the performance of aerial scene classification. However, due to the large amount of parameters and computational cost, it is…
Learning Instance Representation Banks for Aerial Scene Classification
Jingjun Yi, Beichen Zhou
Aerial scenes are more complicated in terms of object distribution and spatial arrangement than natural scenes due to the bird view, and thus remain challenging to learn discrimina…
Minimum-Violation Temporal Logic Planning for Heterogeneous Robots under Robot Skill Failures
Samarth Kalluraya, Beichen Zhou, Yiannis Kantaros
In this paper, we consider teams of robots with heterogeneous skills (e.g., sensing and manipulation) tasked with collaborative missions described by Linear Temporal Logic (LTL) fo…
All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene Classification
Qi Bi, Beichen Zhou, Kun Qin +2
Aerial scene classification remains challenging as: 1) the size of key objects in determining the scene scheme varies greatly; 2) many objects irrelevant to the scene scheme are of…